Huginn - an Active Learning system for Metabolic Network Models development

0. Copyright info: I, Robert Rozanski, the copyright holder of this work, release this work into the public domain. This applies worldwide. In some countries this may not be legally possible; if so: I grant anyone the right to use this work for any purpose, without any conditions, unless such conditions are required by law.

1. Dependencies:

2. Python 3.4.0 with following modules (most of them should be installed by default): * re * sys * time * copy * random * pickle * traceback * subprocess * multiprocessing

3. gringo 3.0.5: http://sourceforge.net/projects/potassco/

4. clasp version 3.0.3: http://sourceforge.net/projects/potassco/

5. XHAIL (System for eXtended Hybrid Abductive Inductive Learning) https://github.com/stefano-bragaglia/XHAIL Note that ./temp/xhail.sh must be edited to point to gringo and clasp

6. Usage: To run existing test cases use command ./evaluator.py > log. The process will print many warnings that can be safely ignored. Important information will be saved in the log file as well as in the ./pickled_archives folder. The latter can be read and analysed using functions from the ./development_analysis.py file.